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arXiv · 1912.08830

ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language

Dave Zhenyu Chen·Angel X. Chang·Matthias Nießner
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Abstract

We introduce the task of 3D object localization in RGB-D scans using natural language descriptions. As input, we assume a point cloud of a scanned 3D scene along with a free-form description of a specified target object. To address this task, we propose ScanRefer, learning a fused descriptor from 3D object proposals and encoded sentence embeddings. This fused descriptor correlates language expressions with geometric features, enabling regression of the 3D bounding box of a target object. We also introduce the ScanRefer dataset, containing 51,583 descriptions of 11,046 objects from 800 ScanNet scenes. ScanRefer is the first large-scale effort to perform object localization via natural language expression directly in 3D.

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Dave Zhenyu Chen, Angel X. Chang, Matthias Nießner. 2019-12-18. ScanRefer: 3D Object Localization in RGB-D Scans using Natural Language. https://arxiv.org/abs/1912.08830

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